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openvinotoolkit · Oct 3, 2024 · 76a53d7 · 76a53d7
1 parent a26ca16
commit 76a53d7
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Showing 2 changed files with 18 additions and 12 deletions.
diff --git a/tests/torch/fx/test_min_max.py b/tests/torch/fx/test_min_max.py
@@ -14,6 +14,7 @@
 import pytest
 
 from nncf.common.graph.graph import NNCFGraph
+from nncf.common.graph.layer_attributes import BaseLayerAttributes
 from nncf.common.graph.transformations.commands import TargetType
 from nncf.quantization.algorithms.min_max.backend import MinMaxAlgoBackend
 from nncf.quantization.algorithms.min_max.torch_fx_backend import FXMinMaxAlgoBackend
@@ -61,19 +62,21 @@ def matmul_metatype(self):
  return PTLinearMetatype
 
  @staticmethod
- def get_conv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]):
+ def get_conv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]) -> BaseLayerAttributes:
  # This method isn't needed for Torch FX backend
- pass
+ return None
 
  @staticmethod
- def get_depthwiseconv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]):
+ def get_depthwiseconv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]) -> BaseLayerAttributes:
  # This method isn't needed for Torch FX backend
- pass
+ return None
 
  @staticmethod
- def get_matmul_node_attrs(weight_port_id: int, transpose_weight: Tuple[int], weight_shape: Tuple[int]):
+ def get_matmul_node_attrs(
+ weight_port_id: int, transpose_weight: Tuple[int], weight_shape: Tuple[int]
+ ) -> BaseLayerAttributes:
  # This method isn't needed for Torch FX backend
- pass
+ return None
 
  def test_get_channel_axes_matmul_node_ov_onnx(self):
  pytest.skip("Test is not applied for Torch FX backend.")

diff --git a/tests/torch/ptq/test_min_max.py b/tests/torch/ptq/test_min_max.py
@@ -13,6 +13,7 @@
 import pytest
 
 from nncf.common.graph.graph import NNCFGraph
+from nncf.common.graph.layer_attributes import BaseLayerAttributes
 from nncf.common.graph.transformations.commands import TargetType
 from nncf.quantization.algorithms.min_max.backend import MinMaxAlgoBackend
 from nncf.quantization.algorithms.min_max.torch_backend import PTMinMaxAlgoBackend
@@ -60,19 +61,21 @@ def matmul_metatype(self):
  return PTLinearMetatype
 
  @staticmethod
- def get_conv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]):
+ def get_conv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]) -> BaseLayerAttributes:
  # This method isn't needed for Torch backend
- pass
+ return None
 
  @staticmethod
- def get_depthwiseconv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]):
+ def get_depthwiseconv_node_attrs(weight_port_id: int, weight_shape: Tuple[int]) -> BaseLayerAttributes:
  # This method isn't needed for Torch backend
- pass
+ return None
 
  @staticmethod
- def get_matmul_node_attrs(weight_port_id: int, transpose_weight: Tuple[int], weight_shape: Tuple[int]):
+ def get_matmul_node_attrs(
+ weight_port_id: int, transpose_weight: Tuple[int], weight_shape: Tuple[int]
+ ) -> BaseLayerAttributes:
  # This method isn't needed for Torch backend
- pass
+ return None
 
  def test_get_channel_axes_matmul_node_ov_onnx(self):
  pytest.skip("Test is not applied for Torch backend.")